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EN
Purpose The aim of the work presented in this paper was the construction of a regression model describing the relationship between the experimentally determined value of the maximum temperature observed during the coal mine waste fire and physico-chemical parameters characterizing the coal mine waste. Methods The model was constructed with the application of the Partial Least Squares method. The experimental data analysed was acquired through the use of a laboratory test stand with a fixed bed reactor and analytical method of gas chromatography. Results The constructed model was characterized by a good fit of the data used in its construction and the strong predictive ability for the new data. It illustrated the significant impact of the content of H and Fe2O3 and trace elements: Co, Cu, Pb, Sr, V and Zn in a sample on the value of the maximum temperature reached during the fire of coal mine waste. Practical implications The practical importance of the work presented is clear in the light of the role of coal in the Polish economy and environmental aspects related to coal mining and the coal-based energy sector, in particularly to coal waste disposal and utilization. The model constructed contributes to the development of methods of self-ignition and fire risk assessment on coal waste dumps by determining the relationship between waste dump fire occurrence, the temperature observed during the fire and the physicochemical parameters characterizing the coal mine waste. Originality/ value The novelty of the study presented in the paper consists in both finding the relationships modelled and the data extraction methods applied in the research field concerned.
EN
Purpose The subject of the research presented in this paper is the analysis of physicochemical parameters characterizing coal mine waste, in terms of their impact on the initialization of the self-ignition phenomenon. Methods The model was constructed with the application of Hierarchical Cluster Analysis complemented with a colour data map enabling the tracing of similarities between the samples of coal mine waste in the space of parameters and between the examined physicochemical parameters in the space of samples. The data set analysed included parameters characterizing coal mine waste collected from 12 various coal mine waste dumps, either in operation or closed, and where thermal effects either took place or were not reported. Results The HCA model constructed and complemented with a colour data map revealed that the tendency of coal mine waste to self-ignite is primarily affected by the contents of moisture, ash, volatile matter, C and S, values of heat of combustion, calorific value and contents of SiO2, Al2O3, K2O, SO3, TiO2, Co, Ni and Rb. Practical implications One of the major environmental hazards associated with the storage of coal mine waste is the possibility of self-ignition. At present, there are no applicable methods of assessment of this risk. The application of Hierarchical Clustering Analysis complemented with a colour data map enabled the analysis of data structures organized in matrix X(m × n) by tracing the similarities between the examined objects in the parameter space and between the measured parameters in the object space, and therefore contributed to the development of procedures of coal mine waste self-ignition risk assessment. Originality/ value The originality of the study presented in this paper comes from finding the parameters affecting the tendency of coal mine waste to self-ignite.
PL
W referacie przedstawiono doświadczenia w zwalczaniu pożaru egzogenicznego składowiska odpadów z kopalni węgla kamiennego. Przedstawiono przebieg likwidacji ognisk pożarowych oraz nową technikę wykorzystującą ciekły CO2 do chłodzenia i inertyzacji ognisk pożarowych w bryle składowiska.
EN
In article is shown case study of extinguishing egzogenic fire in one of Silesian coal mining waste dumps. Besides of presentation of all extinghuishing operation I shown bright new method using liquid CO2 for cooling and atmosphere inertisation inside waste dump.
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